Identification of Virus Encoding MicroRNAs Using 454 FLX Sequencing Platform

2011 ◽  
pp. 81-91 ◽  
Author(s):  
Byung-Whi Kong
Keyword(s):  
Sequencing Platform

scholarly journals Autism Spectrum Disorder (ASD) with and without Mental Regression is Associated with Changes in the Fecal Microbiota

Nutrients ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 337 ◽  
Author(s):  
Julio Plaza-Díaz ◽  
Antonio Gómez-Fernández ◽  
Natalia Chueca ◽  
María Torre-Aguilar ◽  
Ángel Gil ◽  
...  
Keyword(s):  
Intestinal Microbiota ◽  
Present Report ◽  
Principal Component ◽  
Autism Spectrum ◽  
Control Group ◽  
Healthy Group ◽  
Sequencing Platform ◽  
Preliminary Results ◽  
Children With Asd ◽  
Mental Regression

New microbiome sequencing technologies provide novel information about the potential interactions among intestinal microorganisms and the host in some neuropathologies as autism spectrum disorders (ASD). The microbiota–gut–brain axis is an emerging aspect in the generation of autistic behaviors; evidence from animal models suggests that intestinal microbial shifts may produce changes fitting the clinical picture of autism. The aim of the present study was to evaluate the fecal metagenomic profiles in children with ASD and compare them with healthy participants. This comparison allows us to ascertain how mental regression (an important variable in ASD) could influence the intestinal microbiota profile. For this reason, a subclassification in children with ASD by mental regression (AMR) and no mental regression (ANMR) phenotype was performed. The present report was a descriptive observational study. Forty-eight children aged 2–6 years with ASD were included: 30 with ANMR and 18 with AMR. In addition, a control group of 57 normally developing children was selected and matched to the ASD group by sex and age. Fecal samples were analyzed with a metagenomic approach using a next-generation sequencing platform. Several differences between children with ASD, compared with the healthy group, were detected. Namely, Actinobacteria and Proteobacteria at phylum level, as well as, Actinobacteria, Bacilli, Erysipelotrichi, and Gammaproteobacteria at class level were found at higher proportions in children with ASD. Additionally, Proteobacteria levels showed to be augmented exclusively in AMR children. Preliminary results, using a principal component analysis, showed differential patterns in children with ASD, ANMR and AMR, compared to healthy group, both for intestinal microbiota and food patterns. In this study, we report, higher levels of Actinobacteria, Proteobacteria and Bacilli, aside from Erysipelotrichi, and Gammaproteobacteria in children with ASD compared to healthy group. Furthermore, AMR children exhibited higher levels of Proteobacteria. Further analysis using these preliminary results and mixing metagenomic and other “omic” technologies are needed in larger cohorts of children with ASD to confirm these intestinal microbiota changes.

scholarly journals 673 Precision microbiome mapping identifies a microbiome signature predictive of Immune checkpoint inhibitor response across multiple research study cohorts

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A711-A711
Author(s):  
Matthew Robinson ◽  
Kevin Vervier ◽  
Simon Harris ◽  
David Adams ◽  
Doreen Milne ◽  
...  
Keyword(s):  
Gut Microbiome ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitor ◽  
Checkpoint Inhibitor ◽  
Advanced Melanoma ◽  
List Type ◽  
Metagenomic Sequencing ◽  
Genome Database ◽  
Sequencing Platform ◽  
Melanoma Patients

BackgroundThe gut microbiome of cancer patients appears to be associated with response to Immune Checkpoint Inhibitor (ICIs) treatment.1–4 However, the bacteria linked to response differ between published studies.MethodsLongitudinal stool samples were collected from 69 patients with advanced melanoma receiving approved ICIs in the Cambridge (UK) MELRESIST study. Pretreatment samples were analysed by Microbiotica, using shotgun metagenomic sequencing. Microbiotica’s sequencing platform comprises the world’s leading Reference Genome Database and advanced Microbiome Bioinformatics to give the most comprehensive and precise mapping of the gut microbiome. This has enabled us to identify gut bacteria associated with ICI response missed using public reference genomes. Published microbiome studies in advanced melanoma,1–3renal cell carcinoma (RCC) and non-small cell lung cancer (NSCLC)4 were reanalysed with the same platform.ResultsAnalysis of the MELRESIST samples showed an overall change in the microbiome composition between advanced melanoma patients and a panel of healthy donor samples, but not between patients who subsequently responded or did not respond to ICIs. However, we did identify a discrete microbiome signature which correlated with response. This signature predicted response with an accuracy of 93% in the MELRESIST cohort, but was less predictive in the published melanoma cohorts.1–3 Therefore, we developed a bioinformatic analytical model, incorporating an interactive random forest model and the MELRESIST dataset, to identify a microbiome signature which was consistent across all published melanoma studies. This model was validated three times by accurately predicting the outcome of an independent cohort. A final microbiome signature was defined using the validated model on MELRESIST and the three published melanoma cohorts. This was very accurate at predicting response in all four studies combined (91%), or individually (82–100%). This signature was also predictive of response in a NSCLC study and to a lesser extent in RCC. The core of this signature is nine bacteria significantly increased in abundance in responders.ConclusionsAnalysis of the MELRESIST study samples, precision microbiome profiling by the Microbiotica Platform and a validated bioinformatic analysis, have enabled us to identify a unique microbiome signature predictive of response to ICI therapy in four independent melanoma studies. This removes the challenge to the field of different bacteria apparently being associated with response in different studies, and could represent a new microbiome biomarker with clinical application. Nine core bacteria may be driving response and hold potential for co-therapy with ICIs.Ethics ApprovalThe study was approved by Newcastle & North Tyneside 2 Research Ethics Committee, approval number 11/NE/0312.ReferencesMatson V, Fessler J, Bao R, et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 2018;359(6371):104–108.Gopalakrishnan V, Spencer CN, Nezi L, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 2018;359(6371):97–103.Frankel AE, Coughlin LA, Kim J, et al. Metagenomic shotgun sequencing and unbiased metabolomic profiling identify specific human gut microbiota and metabolites associated with immune checkpoint therapy efficacy in melanoma patients. Neoplasia 2017;19(10):848–855.Routy B, Le Chatelier E, Derosa L, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018;359(6371):91–97.

scholarly journals Unmapped exome reads implicate a role for Anelloviridae in childhood HIV-1 long-term non-progression

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Savannah Mwesigwa ◽  
◽  
Lesedi Williams ◽  
Gaone Retshabile ◽  
Eric Katagirya ◽  
...  
Keyword(s):  
Hiv Infection ◽  
Diversity Index ◽  
Strong Association ◽  
Community Diversity ◽  
Added Value ◽  
Sequencing Platform ◽  
Public Health Burden ◽  
Survival Status ◽  
Significant Public Health

AbstractHuman immunodeficiency virus (HIV) infection remains a significant public health burden globally. The role of viral co-infection in the rate of progression of HIV infection has been suggested but not empirically tested, particularly among children. We extracted and classified 42 viral species from whole-exome sequencing (WES) data of 813 HIV-infected children in Botswana and Uganda categorised as either long-term non-progressors (LTNPs) or rapid progressors (RPs). The Ugandan participants had a higher viral community diversity index compared to Batswana (p = 4.6 × 10−13), and viral sequences were more frequently detected among LTNPs than RPs (24% vs 16%; p = 0.008; OR, 1.9; 95% CI, 1.6–2.3), with Anelloviridae showing strong association with LTNP status (p = 3 × 10−4; q = 0.004, OR, 3.99; 95% CI, 1.74–10.25). This trend was still evident when stratified by country, sex, and sequencing platform, and after a logistic regression analysis adjusting for age, sex, country, and the sequencing platform (p = 0.02; q = 0.03; OR, 7.3; 95% CI, 1.6–40.5). Torque teno virus (TTV), which made up 95% of the Anelloviridae reads, has been associated with reduced immune activation. We identify an association between viral co-infection and prolonged AIDs-free survival status that may have utility as a biomarker of LTNP and could provide mechanistic insights to HIV progression in children, demonstrating the added value of interrogating off-target WES reads in cohort studies.

scholarly journals Estimating sequencing error rates using families

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Kelley Paskov ◽  
Jae-Yoon Jung ◽  
Brianna Chrisman ◽  
Nate T. Stockham ◽  
Peter Washington ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Exome Sequencing ◽  
Genome Sequencing ◽  
Variant Calling ◽  
Error Rates ◽  
Sequencing Error ◽  
Whole Genome ◽  
Sequencing Data ◽  
Sequencing Platform ◽  
Whole Exome

Abstract Background As next-generation sequencing technologies make their way into the clinic, knowledge of their error rates is essential if they are to be used to guide patient care. However, sequencing platforms and variant-calling pipelines are continuously evolving, making it difficult to accurately quantify error rates for the particular combination of assay and software parameters used on each sample. Family data provide a unique opportunity for estimating sequencing error rates since it allows us to observe a fraction of sequencing errors as Mendelian errors in the family, which we can then use to produce genome-wide error estimates for each sample. Results We introduce a method that uses Mendelian errors in sequencing data to make highly granular per-sample estimates of precision and recall for any set of variant calls, regardless of sequencing platform or calling methodology. We validate the accuracy of our estimates using monozygotic twins, and we use a set of monozygotic quadruplets to show that our predictions closely match the consensus method. We demonstrate our method’s versatility by estimating sequencing error rates for whole genome sequencing, whole exome sequencing, and microarray datasets, and we highlight its sensitivity by quantifying performance increases between different versions of the GATK variant-calling pipeline. We then use our method to demonstrate that: 1) Sequencing error rates between samples in the same dataset can vary by over an order of magnitude. 2) Variant calling performance decreases substantially in low-complexity regions of the genome. 3) Variant calling performance in whole exome sequencing data decreases with distance from the nearest target region. 4) Variant calls from lymphoblastoid cell lines can be as accurate as those from whole blood. 5) Whole-genome sequencing can attain microarray-level precision and recall at disease-associated SNV sites. Conclusion Genotype datasets from families are powerful resources that can be used to make fine-grained estimates of sequencing error for any sequencing platform and variant-calling methodology.

scholarly journals Noninvasive prenatal detection of fetal sex chromosome abnormalities using the semiconductor sequencing platform (SSP) in Southern China

2021 ◽  
Vol 38 (3) ◽  
pp. 727-734
Author(s):  
Jiexia Yang ◽  
Yaping Hou ◽  
Fangfang Guo ◽  
Haishan Peng ◽  
Dongmei Wang ◽  
...  
Keyword(s):  
Prenatal Diagnosis ◽  
High Risk ◽  
Sex Chromosome ◽  
Southern China ◽  
Prenatal Testing ◽  
Clinical Genetic ◽  
Fetal Sex ◽  
Sequencing Platform ◽  
Cell Free Fetal Dna ◽  
Fetal Aneuploidies

Abstract Background Noninvasive prenatal testing (NIPT) has been widely used to screen for fetal aneuploidies, including fetal sex chromosome aneuploidies (SCAs). However, there is less information on the performance of NIPT in detecting SCAs. Methods A cohort of 47,800 pregnancies was recruited to review the high-risk NIPT results for SCAs. Cell-free fetal DNA (cffDNA) was extracted and sequenced. All NIPT high-risk cases were recommended to undergo invasive prenatal diagnosis for karyotyping analysis and chromosome microarray analysis (CMA). Results A total of 238 high-risk cases were detected by NIPT, including 137 cases of 45,X, 27 cases of 47,XXX, and 74 cases of 47,XYY/47,XXY. Prenatal diagnosis, including karyotyping analysis and CMA, was available in 170 cases. The positive predictive value (PPV) was 30.00% for 45,X, 70.58% for 47,XXX, and 81.13% for 47,XYY/47,XXY. In addition, 13 cases of sex chromosome mosaicism and 9 cases of sex chromosome CNVs were incidentally found in this study. Conclusion Our study showed that NIPT was reliable for screening SCAs based on a large sample, and it performed better in predicting sex chromosome trisomies than monosomy X. Our study will provide an important reference for clinical genetic counseling and further processing of the results.

scholarly journals Detection of Inter-Lineage Natural Recombination in Avian Paramyxovirus Serotype 1 Using Simplified Deep Sequencing Platform

2016 ◽  
Vol 7 ◽  
Author(s):  
Dilan A. Satharasinghe ◽  
Kavitha Murulitharan ◽  
Sheau W. Tan ◽  
Swee K. Yeap ◽  
Muhammad Munir ◽  
...  
Keyword(s):  
Deep Sequencing ◽  
Avian Paramyxovirus ◽  
Sequencing Platform ◽  
Serotype 1 ◽  
Natural Recombination

scholarly journals The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Xueyi Dong ◽  
Luyi Tian ◽  
Quentin Gouil ◽  
Hasaru Kariyawasam ◽  
Shian Su ◽  
...  
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Transcriptomic Analysis ◽  
Statistical Testing ◽  
Rna Seq ◽  
Sequencing Data ◽  
Short Read ◽  
Sequencing Platform ◽  
Long Read

Abstract Application of Oxford Nanopore Technologies’ long-read sequencing platform to transcriptomic analysis is increasing in popularity. However, such analysis can be challenging due to the high sequence error and small library sizes, which decreases quantification accuracy and reduces power for statistical testing. Here, we report the analysis of two nanopore RNA-seq datasets with the goal of obtaining gene- and isoform-level differential expression information. A dataset of synthetic, spliced, spike-in RNAs (‘sequins’) as well as a mouse neural stem cell dataset from samples with a null mutation of the epigenetic regulator Smchd1 was analysed using a mix of long-read specific tools for preprocessing together with established short-read RNA-seq methods for downstream analysis. We used limma-voom to perform differential gene expression analysis, and the novel FLAMES pipeline to perform isoform identification and quantification, followed by DRIMSeq and limma-diffSplice (with stageR) to perform differential transcript usage analysis. We compared results from the sequins dataset to the ground truth, and results of the mouse dataset to a previous short-read study on equivalent samples. Overall, our work shows that transcriptomic analysis of long-read nanopore data using long-read specific preprocessing methods together with short-read differential expression methods and software that are already in wide use can yield meaningful results.

The mycobiome of the oral cavity in healthy dogs and dogs with periodontal disease

2022 ◽  
pp. 1-8
Author(s):  
Brook A. Niemiec ◽  
Jerzy Gawor ◽  
Shuiquan Tang ◽  
Aishani Prem ◽  
Janina A. Krumbeck
Keyword(s):  
Oral Cavity ◽  
Periodontal Disease ◽  
Dna Sequencing ◽  
Fungal Species ◽  
Next Generation ◽  
Data Set ◽  
Next Generation Dna Sequencing ◽  
Sequencing Platform ◽  
The Family ◽  
Healthy Dogs

Abstract OBJECTIVE To investigate the mycobiome of the oral cavity in healthy dogs and dogs with various stages of periodontal disease. ANIMALS 51 dogs without periodontal disease (n = 12) or with mild (10), moderate (19), or severe (10) periodontal disease. PROCEDURES The whole maxillary arcade of each dog was sampled with a sterile swab, and swabs were submitted for next-generation DNA sequencing targeting the internal transcribed spacer 2 region with a commercial sequencing platform. RESULTS Fungi were detected in all samples, with a total of 320 fungal species from 135 families detected in the data set. No single fungal species was found in all samples. The 3 most frequently found fungal species were Cladosporium sp (46/51 samples), Malassezia restricta (44/51 samples), and Malassezia arunalokei (36/51 samples). Certain fungi, specifically those of the family Didymellaceae, the family Irpicaceae, and the order Pleosporales, were significantly associated with different stages of periodontitis. Mycobial analysis indicated that Cladosporium sp could be considered part of the core oral cavity mycobiome. CONCLUSIONS AND CLINICAL RELEVANCE Results highlighted that fungi are present in the oral cavity of dogs and are characterized by substantial species diversity, with different fungal communities associated with various stages of periodontal disease. The next-generation DNA sequencing used in the present study revealed substantially more species of fungi than previous culture-based studies.

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